Company Overview

The hiring organisation operates within financial technology and foreign exchange services, using data-driven analysis to support risk oversight and operational decision-making. Its risk function focuses on developing reliable analytical methods that help evaluate counterparty creditworthiness, measure exposure, and identify potential financial vulnerabilities.

Role Summary

The Credit Risk Modelling Analyst will develop, validate, and maintain analytical models used to assess credit risk across FX-related client and counterparty portfolios. The position combines quantitative analysis, financial risk assessment, and data management to improve credit monitoring, risk forecasting, and decision-making.

Key Responsibilities

• Develop and maintain credit risk models for counterparty assessment, exposure estimation, and credit risk classification.

• Analyse historical credit performance, counterparty financial data, and exposure trends to identify relevant risk drivers.

• Build and test scoring methodologies and early-warning indicators for potential credit deterioration.

• Conduct model validation, back-testing, sensitivity analysis, and performance monitoring.

• Evaluate the impact of foreign exchange volatility and changing counterparty conditions on credit exposure.

• Use statistical techniques to identify patterns, assess model assumptions, and improve predictive accuracy.

• Prepare model documentation, analytical reports, and recommendations for risk management stakeholders.

• Work with data engineering, treasury, and credit risk teams to improve data quality and model integration.

• Support internal model governance, audit requests, and applicable regulatory reporting requirements.

Requirements and Qualifications

• Bachelor’s degree in Statistics, Mathematics, Econometrics, Computer Science, Finance, or a related quantitative discipline.

• Relevant experience in credit risk modelling, quantitative risk analysis, financial analytics, or model validation.

• Strong understanding of credit risk concepts, statistical modelling, and quantitative analysis.

• Proficiency in Python or R and advanced SQL; experience with statistical or machine learning libraries is an advantage.

• Experience with model testing, data validation, performance measurement, and technical documentation.

• Familiarity with FX markets, counterparty risk, or financial services data is highly desirable.

• Strong problem-solving skills and the ability to communicate technical findings clearly.

Benefits

• Fully remote working opportunity within Estonia.

• Opportunity to work on quantitative risk models supporting FX financial services.

• Professional development in credit analytics, statistical modelling, and risk technology.

• Collaboration with multidisciplinary teams across finance, data, and technology.

• Exposure to practical model governance and financial risk management challenges.

Application Instructions

Interested candidates should submit a current CV highlighting their quantitative background, credit risk modelling experience, and relevant programming skills. Applicants may also include a brief summary of a modelling or risk analytics project demonstrating their technical approach and analytical judgement. Applications should be submitted through the official application channel provided by the hiring organisation.

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